Improve shiny tutorial clarity

6 files changed, 5 insertions, 7 deletions

diff --git a/DESCRIPTION b/DESCRIPTION
index 35c334c..e84e76d 100644
--- a/DESCRIPTION
+++ b/DESCRIPTION
@@ -1,6 +1,6 @@
 Package: unmarked
 Version: 1.2.5.9008
-Date: 2022-11-15
+Date: 2022-11-21
 Type: Package
 Title: Models for Data from Unmarked Animals
 Authors@R: c(
diff --git a/inst/shinyPower/server.R b/inst/shinyPower/server.R
index bb49064..75b27c0 100644
--- a/inst/shinyPower/server.R
+++ b/inst/shinyPower/server.R
@@ -37,7 +37,6 @@ get_coefs <- function(input, nulls=FALSE){
   parbase <- "coef_"
   if(nulls) parbase <- "null_"
   pass <- reactiveValuesToList(input)
-  pass$shinymanager_where <- NULL
   inp_sub <- pass[grepl(parbase,names(pass), fixed=TRUE)]
   inp_sub <- pass[!is.na(names(inp_sub))]
   names(inp_sub) <- gsub(parbase, "", names(inp_sub))
@@ -64,7 +63,6 @@ get_design_ui <- function(input, default, name){
 
 get_design <- function(input){
   pass <- reactiveValuesToList(input)
-  pass$shinymanager_where <- NULL
   inp_M <- unlist(pass[grepl("design_sites_",names(pass),fixed=TRUE)])
   inp_M <- inp_M[1:input[["ndesign_sites"]]]
   inp_J <- unlist(pass[grepl("design_obs_",names(pass),fixed=TRUE)])
diff --git a/inst/shinyPower/ui.R b/inst/shinyPower/ui.R
index bf59c3a..636c629 100644
--- a/inst/shinyPower/ui.R
+++ b/inst/shinyPower/ui.R
@@ -1,5 +1,4 @@
 library(shiny)
-library(shinymanager)
 
 inline_wrap <- function(f, ...){
   out <- f(...)
@@ -50,4 +49,3 @@ ui <- fluidPage(
 )
 
 ui
-#secure_app(ui)
diff --git a/vignettes/figures/poweranalysis-effectsizes.png b/vignettes/figures/poweranalysis-effectsizes.png
index e91f662..6435dae 100755..100644
--- a/vignettes/figures/poweranalysis-effectsizes.png
+++ b/vignettes/figures/poweranalysis-effectsizes.png
diff --git a/vignettes/powerAnalysis.Rmd b/vignettes/powerAnalysis.Rmd
index 9c67344..f2cce35 100644
--- a/vignettes/powerAnalysis.Rmd
+++ b/vignettes/powerAnalysis.Rmd
@@ -891,7 +891,8 @@ It's a good idea to simulate the template model with the largest sample size you
 Next you must set the effect sizes you want to test in the power analysis.
 Each submodel has its own section.
 In this case state = occupancy and det = detection.
-Effect sizes for all parameters in the model default to 0; you'll want to change at least one of them in most cases.
+Effect sizes for all parameters in the model default to 0; you'll want to change them to reflect your expectations about the study system.
+Here we are simulating datasets with an elevation effect of 0.4 (on the logit scale), with occupancy and detection intercepts equal to 0 (equivalent to probabilities of 0.5).
 
 ![](figures/poweranalysis-effectsizes.png)
 
diff --git a/vignettes/powerAnalysis.Rmd.orig b/vignettes/powerAnalysis.Rmd.orig
index d923964..fad2fb0 100644
--- a/vignettes/powerAnalysis.Rmd.orig
+++ b/vignettes/powerAnalysis.Rmd.orig
@@ -581,7 +581,8 @@ It's a good idea to simulate the template model with the largest sample size you
 Next you must set the effect sizes you want to test in the power analysis.
 Each submodel has its own section.
 In this case state = occupancy and det = detection.
-Effect sizes for all parameters in the model default to 0; you'll want to change at least one of them in most cases.
+Effect sizes for all parameters in the model default to 0; you'll want to change them to reflect your expectations about the study system.
+Here we are simulating datasets with an elevation effect of 0.4 (on the logit scale), with occupancy and detection intercepts equal to 0 (equivalent to probabilities of 0.5).
 
 ![](figures/poweranalysis-effectsizes.png)